# 卷积神经网络 卷积核
import torch
import torch.nn.functional as F

input = torch.tensor([[1, 2, 0, 3, 1], 
                      [0, 1, 2, 3, 1], 
                      [1, 2, 1, 0, 0],
                      [5, 2, 3, 1, 1],
                      [2, 1, 0, 1, 1]])

kernel = torch.tensor([[1, 2, 1], 
                        [0, 1, 0], 
                        [2, 1, 0]])

print(input.shape)
print(kernel.shape)

input = torch.reshape(input, (1, 1, 5, 5))
kernel = torch.reshape(kernel, (1, 1, 3, 3))

print(input.shape)
print(kernel.shape)

output = F.conv2d(input, kernel, stride=1)
print(output)

output = F.conv2d(input, kernel, stride=1, padding=1)
print(output)


